Friday, July 15, 2016

Edit Note, 7.16.16: I've added two substantial paragraphs near the end of the section, "Computing, Abstract and Real." Check the Golumbia tag for further thoughts, as I'm in the processing of adding new material to a revised version of this piece.

As many of you know, David Golumbia is one of three authors of a recent article that that offered a critique of the digital humanities (DH), Neoliberal Tools (and Archives): A Political History of Digital Humanities [1]. The article sparked such vigorous debate within the DH community that I decided to investigate Golumbia’s thinking. I’ve known about him for some time but had not read his best known book:

David Golumbia. The Cultural Logic of Computation. Harvard University Press, 2009.

I’ve still not read it in full. But I’ve read enough to arrive at a conclusion.

Thus this piece is not a book review. I focus on the second chapter, “Chomsky’s Computationalism,” with forays into the first, “The Cultural Functions of Computation,” and a look at the fourth, “Computationalist Linguistics.”

Why Chomsky?

Chomsky is one of the seminal thinkers in the human sciences in the last half of the twentieth century. The abstract theory of computation is at the center of his work. His early work played a major role in bringing computational thinking to the attention of linguists, psychologists, and philosophers and thus helped catalyze the so-called cognitive revolution. At the same time Chomsky has been one of our most visible political essayists. This combination makes him central to Golumbia’s thinking, which is concerned with the relationship between the personal and the political as mediated by ideology. Unfortunately his understanding of Chomsky’s thinking is so tenuous that his enterprise is flawed from its inception. I am not prepared to say whether or not the rest of the book redeems its dismal beginning.

First I consider the difference between abstract computing theory and real computing, a distinction to which Golumbia gives scant attention. Then I introduce his concept of computationalist ideology and criticize his curious assertion that computational linguistics “is almost indistinguishable from Chomskyan generativism” (p. 47). From there I move to his treatment of the Chomsky Hierarchy, pointing out that it is a different kind of beast from hierarchical power relations in society. The last two sections examine remarks that are offered almost as casual asides. The first remark is a speculation about the demise of funding for machine translation in the late 1960s. Golumbia gets it wrong, though he lists a book in his bibliography that gets it right. I conclude with some corrective observations in response to his off-hand speculation about the ideological demographics of linguistics.

Computing, Abstract and Real

I want to start by making a standard distinction between computing in the abstract and embodied computation, “real” if you will. This distinction is important in the context of Golumbia’s book because Chomsky concerned himself only with computing in the abstract. In contrast, computational linguistics (hereafter CL) is about real computing, though computational linguists may avail themselves of abstract theory as an analytical tool. The so-called Chomksy Hierarchy, which we’ll get to a bit later, is one of those analytical tools, and an important one.

Real computation is a physical activity. It is bounded in time – it must come to an end or it has failed – and space – it is realized in physical stuff, Descartes’ res extensa. In decades stretching from the present back into the 19th century, that physical stuff has been some kind of mechanical, electrical, or electronic system. Starting roughly in the middle of the previous century various disciplines have been entertaining the idea that computation might also be realized in animal nervous systems, the human brain in particular, and even the molecular machinery of DNA and RNA.

Computing in the abstract is not physically realized. It is a mathematical activity concerned with purely abstract machines, often called automata. The abstract theory is concerned about the powers of abstract machines as a function of the symbols available to a machine, the states the machine can take, and the operations through which the machine moves from one state to the next.

We can appreciate the difference between real and abstract computing with a relatively simple example, the contrast between tic-tac-toe on the one hand and chess on the other. Abstractly considered they are the same kind of game, and a trivial one at that. They are both finite. As real activities, that is, as activities realized in physical matter, they are quite different. Tic-tac-toe remains trivial, though perhaps not so for a six-year old; but chess becomes profoundly difficult and challenging for even the most brilliant of humans.

How can this be? Let us start with tic-tac-toe. It is played on a space consisting of nine cells in a 3-by-3 array. Each space can be in one of only three states: empty, filled with an X, filled with an O. The game starts with an empty array and concludes either when 1) we have a row or diagonal of three symbols of one kind or 2) when an X or O occupies each cell. The board is finite, the symbol set is finite, and there is a set of well-defined end conditions. That makes the game as a whole finite.

This finite character is not changed by using a larger array, say five by five. But the game becomes a little more difficult. A player who has mastered the 3-by-3 game may have to think a bit about the 5-by-5 game. What about 100 by 100? It’s still finite, but perhaps more challenging. Could it thus be the case that a mere quantitative change, number of possible game states, can lead to a qualitative change in the means necessary to negotiate them?

Now consider chess. The board is finite, eight-by-eight. Each player starts with a finite number of pieces, 16 each, though they are of six kinds, each having different powers: king (1), queen (1), knight (2), bishop (2), rook (2), and pawn (8). That means that at any given time each board space will be in one of 13 states: empty, occupied by one of six white pieces, or occupied by one of six black pieces. It is possible, however, that as the board is emptied of pieces a state will be reached where neither player is able to defeat the other and they are unwilling to declare a draw. What then? If the players have agreed to the rules established by the FIDE (Fédération Internationale des Échecs), then one of several conventions will result in a draw. That makes chess a finite game.

Just like tic-tac-toe.

Now, and this is very important, these two games are said to be finite, not simply because their constituent elements (game board, pieces, rules) are finite, but because the total number of games generated with those elements is finite. That’s why the ending conventions for chess are so important. An end game in which the two opponents chase each other around the board without ever reaching checkmate or a draw (the two end states) is boring and uninteresting. But it is not finished. If chess admitted such games, then chess would not be a finite game. Why not? Because, when played that way, chess has no well-defined end state. Some chess games will go on forever, at least in theory. In reality, of course, at least one of the players will either give up or die and that will end the game.

Now we can introduce Chomsky. Using methods derived from mathematics, he argued that natural languages are infinite in a way that chess (as played with stop conventions) is not, despite being constituted by a finite number of elements. Any language is capable of producing an infinite number of grammatical sentences. But it does so with only finite resources, words and rules for combining them. You can argue that thinking about language in this way is not intellectually productive, but to make that argument you need to understand it. Golumbia does not.

Returning to tic-tac-toe, writing a computer program that can play it well is something that can be done in a beginning course in computer programming. I wrote such a program – one of the few I’ve written, as I am no programmer – when I took such a course back in the Jurassic Era, the Fall of 1967 I believe. Writing a computer program to play a good game of chess, that has proven more challenging.

Programming a computer to do high quality translation from one language to another, the problem that initiated the study of computational linguistics back in the early 1950s, that remains challenging, more so than chess. We do not know when, if ever, that will be done. A low quality approximation, however, is freely available to anyone with a computer and access to the Internet. These translations have their uses, but I wouldn’t want to use one for a legal document or a work of poetry.

With that let us turn to Golumbia.

Computationalism

Golumbia is not interested in computing as such, whether real or abstract. Rather, he is interested in an ideological formation called computationalism. To begin (p. 1):

I argue that the current vogue for computation takes this old belief system – that something like rational calculation might account for every part of the material world, and especially the social and mental worlds – and repurposes it in such a way so as to give every appearance of being something very new.

The term itself (p. 2):

...my concern is that belief in the power of computation – a set of beliefs I call here computationalism – underwrites and reinforces a surprisingly traditionalist conception of human being, society, and politics. In other registers, we might imagine these views to have long been abandoned, in large part because their faults as part of a total account of human being have been long ago demonstrated conclusively.

In contrast (p. 21):

...a rough approximation of my thesis might be that most of the phenomena in each sphere [covered in this book], even if in part characterizable in computational terms, are nevertheless analog in nature. They are gradable and fuzzy; they are rarely if ever exact, even if they can achieve exactness. The brain is analog; language is analog; society and politics are analog.

Yes, analog. I note, however, that analog DOES NOT stand in contrast to computing, as Golumbia’s statement suggests. While most of the analog world, if you will, has little to do with computing, once we consider real computing, analog and digital become alternative means of physical embodiment, with hybrid strategies both possible and common. For a sophisticated primer I suggest John von Neumann’s last and incomplete book, The Computer and the Brain (1958) – a précis is available online.

Moreover, the digital world has devoted enormous time and effort to developing digital approximations of analog phenomena. Why? Because the real world if full of the gradable and the fuzzy and digital computing has to be useful in the real world.

Let us now consider this passage (pp. 46-47):

In the broad pursuit of CL, which is almost indistinguishable from Chomskyan generativism but nevertheless gives itself a different name, the computer and its own logical functions are taken as a model for human language to begin with, so that computer scientists and Artificial Intelligence (AI) researchers use what they have learned to demonstrate the formal nature of human language.

This is, to put it mildly, nonsense. Why? Because, as Golumbia does point out here and there, Chomsky’s interest in computation is purely abstract. He is not interested in actually computing with or on language. He did not and does not devise algorithms (computing procedures) nor work with programmers to implement those algorithms. Computational linguists must do both.

Are Chomsky’s ideas present in CL? Sure, but Chomsky has had many ideas and they have been broadly influential, which is why he is an important figure generally, and important for Golumbia’s argument in particular. But, as we’ll see a bit later, CL began before Chomsky published Syntactic Structures in 1957. His ideas were probably not as influential within CL as they were in were in linguistics in general, not so much because CL was already under way, but because computational linguistics deals in real computation and presents problems of capacity – of time (CPU cycles) and storage – that don’t exist in the abstract realm.

In fact, several important figures within CL developed ideas in opposition to Chomsky. David Hays was one of them. He led a first-generation effort in machine translation (MT) at the RAND Corporation during the 1950s and 1960s. MT was the precursor to CL. As Martin Kay has written [2]:

There is nothing trite in characterizing David Glen Hays (1928-1995) as the father of his field. He invented the very name computational linguistics, was the main force behind the foundation of the Association for Computational Linguistics – originally the Association for Machine Translation and Computational Linguistics – and established and set his seal on the International Committee on Computational Linguistics and the series of conferences it organizes.

Martin Kay, though a researcher of the highest reputation, is necessarily biased in his assessment. Hays had hired him to RAND and continued the relationship after both had left RAND. Kay was English and had received his initial training in computational linguistics at Cambridge under Margaret Masterman, who had studied under Wittgenstein [3].

When I worked with Hays I was a student in the English Department at SUNY Buffalo; Hays was in the Linguistics Department (of which he had been founding chair). His semantic model was the conceptual heart of my dissertation work. He was also editor of the American Journal of Computational Linguistics (now simply Computational Linguistics) and, for three years, I was its bibliographer. In that capacity I scanned the relevant journal literature – in computational linguistics, linguistics, artificial intelligence, cognitive psychology, library science, computer science, automata theory, and whatever else seemed pertinent – and examined the many technical reports the journal received. I then prepared abstracts of these materials.

That was four decades ago. The field has changed a lot since then, and I’ve not kept up. But I am aware of broad trends and take a look at the technical literature every now and then.

Given my involvement in the field one might reasonably ask whether or not I am a computationalist in the sense that Golumbia uses the term. I think not. For one thing I certainly don’t believe that “rational calculation might account for every part of the material world, and especially the social and mental worlds” nor did Hays. Nor did we believe that the brain is only digital. In fact we spent a great deal of time working on a theoretical scheme for interaction between analog and digital processes [4].

More generally I note that one can be deeply engaged in the computational investigation of language, or the creation of language tools and applications, without having any particular beliefs about the scope of rational calculation in the world and the nature of human thought. The computing tools themselves, the physical machines, the software, make their own demands and have their own affordances. If those demands and affordances are consistent with your beliefs about the ultimate nature of the world, fine. But if they are at odds with your beliefs, well, you can still take pleasure in the challenge of building things – ideas, models, practical applications – with those tools.

With that in mind, let us turn to Golumbia’s account of the Chomsky Hierarchy.

Hierarchy in Theory and Society

Golumbia introduces the Chomsky hierarchy by asserting, “the ideological burden of Chomsky’s work on CFGs is to establish the existence of a hierarchy which can contain both natural and logical languages to a single system” (pp. 37-38). At this point he has not told us what CFGs are though he does so in a footnote anchored a bit later on page 38. CFGs are Context-Free Grammars, a type of grammar within the hierarchy, though Golumbia writes as though “CFG” is a covering term for the entire hierarchy.

But he never really tells us what the hierarchy is. It’s a bit technical so for the purposes of this essay I am going to offer a crude analogy. Let us imagine several types of arithmetic. In the simplest scheme, addition is the only permissible process. Call this Type-3. Type-2 is more powerful, if you will, because it also admits subtraction. Type-1 is more powerful still and includes multiplication. With Type-0 arithmetic we have the full set of arithmetic operations: addition, subtraction, multiplication, and division. These types form a hierarchy in the sense that a higher type (one with a lower number, the convention Chomsky adopted) can perform a wider range of operations than a lower type.

Chomsky’s hierarchy is defined in terms of rules that operate on strings of characters [5]. The characters of most interest to linguists, of course, are those used to represent words in a language. In Chomsky’s scheme a Type-0 grammar, the most powerful type, is said to be unrestricted. Such grammars have the power of a universal Turing machine. A Type-1 grammar is said to be context-sensitive while a Type-2 grammar is context free (CFG). Type-3 grammars are said to be regular grammars. Just what these terms mean is not important at the moment. We can move on without knowing that. What’s important is that the relations among these types are roughly like the relations among our types of arithmetic. Higher types can do more than lower types.

What interests Golumbia is the relationship between this hierarchy and Chomsky’s politics (p. 52):

It may be surprising too to learn that Chomsky’s principal contribution to computer science – perhaps even one of the chief goals for which he was receiving funding – is explicitly called a “hierarchy,” that especially exact and abstract trope of ordered, striated power. Chomsky’s political work has long been opposed to just such formations, strongly favoring distributed and rhizomatic syndicates to empires and kingdoms. But the hierarchy is critical for keeping logical (and so computational) languages on the same plane with natural languages, the ones Chomsky continues to have in mind. [...] In his overt politics, Chomsky opposes the necessity of hierarchies in the strongest way, while his intellectual work is predicated on the intuitive notion that language and cognition require hierarchies. For Chomsky there must be no connection between these two spheres, despite the obvious (but structural and unconscious) ways in which they seem to connect.

What are we to make of these assertions?

The concept of hierarchy employed in Chomsky’s linguistics is fundamentally different from the concept of hierarchy employed in understanding social and political systems. In the second case we talking about the power that one person (or organization) has over another. This relationship can be formal, as in a military chain of command or a corporate structure; or it can be informal, as in the ability of a wealthy person of high social status to asymmetrically influence the life of a poor person of low state. We are also interested in the powers exercised by groups of people, as in the Occupy protest movement organized around the 1% vs. the 99%.

The Chomsky hierarchy is nothing like this. Type-0 grammars do not have a platoon of Type-1 grammars at their disposal. A Type-1 grammar cannot imprison a Type-2 grammar that fails to parse a phrase. Nor can a group of Type-3 grammars band together to attack a country palace in which Type-1 grammars are having illicit conjunctions while the Type-0 monarch uses his compound claws to dangle his participle before his Type-2 dependents. Hierarchy in this sense has nothing to do with social-political power. There is thus nothing in the least bit puzzling about linguist Chomsky using one type of hierarchy as an analytic instrument while citizen Chomsky opposes the other type of hierarchy in political relations. They are different kinds of things.

The Demise of MT: Blow-Back on Chomsky?

Now let us consider a remark Golumbia has made about the practical politics of computational linguistics (p. 38):

If throughout his life Chomsky has endured others seeing what they want to in his work, it seems clear that what happens in this case is not just computer scientists but an entire community of technically-minded intellectuals seeing in Chomsky’s work precisely the potential to do what Chomsky disclaims – to bring human language under computational control. Surely it is not leap to think that this is exactly what the defense-industrial establishment sees in Chomsky’s program which attracts the attention of precisely the logicians, computer scientists, and technicians who were looking for someone to lead them down the glory road to “machines speaking.” By the time funding for such projects has largely dried up in the late 1960s–perhaps in the face of the pullback from Vietnam and Chomsky’s outspoken opposition to it–Chomsky writes that “machine translation and related enterprises...seemed to me pointless as well as probably quite hopeless...”

Golumbia is driving at the idea that, while the abstract idea of computation has been central to Chomsky’s thinking, Chomsky had no interest in machine translation and related pursuits.

What struck me about Golumbia’s statement, though, is the phrase between the dashes, which I initially read as:

...perhaps in the face of the pullback from Vietnam and Chomsky’s outspoken opposition to [that pullback] ...

Given Chomsky’s strong and very public opposition to the war, however, that reading makes no sense. I decided that this is the more likely reading:

...perhaps in the face of the pullback from Vietnam and Chomsky’s outspoken opposition to [the war in Vietnam]...

But why would Golumbia advance this speculation? What’s the connection between Chomsky’s opposition to the war in Vietnam and the federal government’s decision to stop funding work in machine translation? Is Golumbia suggesting retaliation against Chomsky’s public criticism?

I have no idea what Golumbia has in mind, but there is a standard and well-known account of why machine translation (MT) was defunded. It has nothing to do with Chomsky or the war in Vietnam and can be found in a book listed in Golumbia’s bibliography: John Hutchins, Machine Translation: past, present, future (1986).

Before I rehash that story, however, I want to say a bit about the early days of machine translation. Golumbia discusses the very earliest work, stemming from suggestions by Warren Weaver, in chapter 4, “Computationist Linguistics,” but once he’s told that story he skips to the present, more or less, and discusses a variety of work. The early days of MT are important, however, because the work started before Chomsky had published.

Hutchins discusses over a dozen MT research groups during the years between 1950 and 1966. Some were of a more theoretical orientation, some more “roll up our sleeves and get dirty” (my phrase). But having a theoretical bent does not preclude a commitment to empiricism, not in the MT world. If you are going to theorize about language and translation, don’t you need a detailed descriptive account of the materials you are theorizing about?

I will confine my remarks to two of these groups, the work at the RAND Corporation under David Hays and the work a University of California at Berkeley under Sydney Lamb. I chose these two because I’m familiar with the work of these two men. As I said at the outset, I was a student of Hays’s in the mid-1970s; more recently I have worked with Lamb’s theory in unpublished work of my own and have had some correspondence with him.

According to Hutchins, both groups did considerable descriptive work [6]. The RAND group conducted a statistical analysis of a Russian corpus (which, according to Martin Kay, reached a million words [2]). The structure of each sentence was hand-annotated by Russian specialists. The Berkeley group developed a 300,000 word Russian-English dictionary. Both groups developed language models along lines different from the phrase-structure models favored by Chomsky. Following Tesnière, Hays adopted dependency grammar while; Lamb developed stratificational grammar, partly inspired by Hjelmslev. Other groups developed their own models.

In short, Chomsky was not the only game in town. Different theoretical models were developed and deployed and there was a lot of empirical work that is quite different in spirit from Chomsky’s work. As for just when and how Chomsky’s work would be felt in computational linguistics, I’m not sure, but the impression I have from talking with Hays is that it was relatively late.

And that brings us back to our starting point, the defunding of work on MT [7]. Early in the 1960s this work came under increasingly public criticism. By that time the promised practical results had not materialized. Late in 1963 the director of the National Science Foundation asked the National Academy of Sciences to create a committee to advise the government on future funding for MT. The Automatic Language Processing Advisory Committee (ALPAC) was impaneled in 1964 (David Hays was a member). Their report was published in 1966 and, in the words of Martin Kay, in effect recommended, “resources should therefore be withdrawn from machine translation as a practical engineering enterprise and directed instead to linguistics and especially to the scientific study of language processing” [2].

The government took the first recommendation and ignored the second. That was the end of government funding for research in computational linguistics, as the field had come to be called [3]. There may well have been bureaucrats and generals rabid with desire for a translating machine, but they were happy enough to pull the plug when reality continued to fall short of desire.

Why then did Golumbia offer his admittedly weak speculation (“perhaps”) that Chomsky’s criticism of the war in Vietnam had something to do with it? I do not know, but the effect of such speculation is to exaggerate Chomsky’s importance to practitioners of enterprises, MT and then CL, in which he had little interest. Moreover, to the extent that Golumbia is hoping that his critique will be useful in practical affairs in ameliorating the effects of computationalism, this shot at the demise of MT funding does not speak well of his political judgment.

White Males, Past Presidents of the ACL, and a Specious Binary

Finally, I want to consider a set of remarks that could easily be ignored as casual asides. Consider this passage (p. 40):

Notably, the thinkers who were most struck by these theories [Chomsky’s] were almost exactly the same ones who were so possessed by computers: they were generally white, highly educated males, and rarely female or people of color. They were also, for the most part, not linguists.

It remained for a generation of white men who were not trained in Bloomfieldian and other anthropological theories of language [...] to pick up Chomsky’s theories and turn them into the mainstream of the discipline. Although there are many exceptions, it is still true that Chomskyan approaches have tended to attract white men (and also men from notably imperial cultures, such as those of Korea and Japan), and that women and minority linguists have tended to favor non-Chomskyan approaches.

We have a set of empirical statements about what kinds of linguistic theories are favored by what kinds of people. But Golumbia offers no evidence for these statements. Does he want us to accept these assertions on his authority? I hope not. Or perhaps he regards them as obvious truisms that are so well known to his audience that evidence is not required. This is tricky, to which I’ll return in a minute.

My best guess, and it is only that, is that while these assertions appear to be empirical, their performative valence, if you will, is different. They are being offered as shibboleths to remind his readers of his cultural studies bona fides. He is telling us that there is an ideological attraction between Chomsky’s ideas and the social and political interests of white males, but not the interests of women or people of color.

Let’s take another look. What we know, more or less, is that American academic culture is mostly white and mostly male, and it was more so in the 50s and 60s when Chomsky’s work first became known than it is now. Given that, though, what’s the point of even asserting that Chomsky’s ideas were taken up by “white, highly educated males”? That after all, was and still is most of the academic population.

With that in mind I decided to investigate Golumbia’s bibliography, which is 18 pages long (pp. 233-250). I’ve done a quick and crude tabulation of the authors in which I identified them as male or female based on their names. In some cases I couldn’t make a classification, either because Golumbia listed only a first initial or because I didn’t know how to classify the first name. There are over 300 authors, some with multiple publications and some publications with multiple authors; 81% are male, 13% female, and I couldn’t classify 6%. In those cases where I had some reasonable recognition of the author, most of them seemed to be white. But I didn’t attempt to tabulate that. Obviously, for example, Gayatri Charkravorty Spivak is neither white nor male and Alan Turing is white, male, and gay.

Some of these individuals are listed because they are being critiqued for their computationalist ideas. Others are cited because Golumbia is using their ideas in his critique. And some are cited for other reasons. I have no idea about how to apportion these male and female thinkers according to their affinity for or rejection of computationalism, but Golumbia would have a hard time making his argument without being able to call on the ideas of white men such as Heidegger, Derrida, Foucault, Deleuze, Guattari, Jameson, Althusser, Lacan, De Landa, and many others. On the whole I am not inclined to think that being educated, white, and male is a very strong index of ideological proclivities in this domain, not for this population of highly specialized intellectuals.

What about women in linguistics? I did a little poking around in search of anecdotal evidence. I found this recent appreciation for the late Jane Robinson, a first generation computational linguist who became president of the Association for Computational Linguistics (ACL) in 1982. I don’t know quite where to place her on the Chomsky-or-not spectrum but she worked with David Hays at RAND and was interested in dependency theory. Two of the authors of the obituary are women, Barbara Grosz (Harvard) and Eva Hajicova (Charles University in Prague). Note that Charles University was the locus of the fabled Prague School of linguists, where Roman Jakobson once sojourned. Hajicova is also a past president of ACL, as is the third author, Aravind Joshi (University of Pennsylvania).

The piece mentions two other distinguished women, Joyce Friedman and Karen Sparck Jones, both past presidents of ACL. It also mentions Susumo Kuno, who, though male, is also Japanese, and – you guessed it – a past ACL president. I do not know whether or not he is one of those imperial Japanese Golumbia has warned us about, but I remember hearing his name uttered in tones of hushed respect when I was at Buffalo in the 1970s. Other past ACL presidents are also mentioned.

All of these women (and one Japanese man) are not merely linguists, but computational linguists. Whatever their theoretical predilections, they actually do computational work while Chomsky does not. Are they computationalist as well? Do they realize that their work “is almost indistinguishable from Chomskyan generativism,” to use Golumbia’s formulation? I do not know. But I doubt that they would find that formulation congenial.

I also placed a query on the Facebook page of John Lawler, a linguist who retired from the University of Michigan a few years ago. Here are some snippets from their responses:

Avery Andrews: He's wrong about the history too; many linguists were interested from early days, although many of them became repelled by various aspects of Chomsky's behavior.‬‬‬‬

Pauline Jacobson: And most everyone in those days doing most academic things where white and males, but I do think that reasonably early on there were more women doing syntax (of the Chomskyan variety) than there were women in many other technical fields. I don't have statistics, and it's just an impression, but the author sounds very off base here.‬

A bit later Jacobson remarks, “’Chomskyan linguistics’ (whatever on earth that means - I HATE that category, and equally well hate ‘non (or anti) Chomskyan linguistics’).” We’ve got a false binary here, Chomsky vs. not-Chomsky. Is it the sign of an ideological formation that is hostile to the contemporary study of language? [Note that Jacobson made an important longer remark about linguistics, math, and women that I have placed in an appendix.]

For one thing, Chomsky’s ideas have changed substantially other the years – something Golumbia knows and mentions in the book. For another thing, one can use some of his ideas but not others. The Chomsky hierarchy, to consider only one example, has wide use both within linguistics and in computer science, but one can use it for analytic purposes without adopting Chomsky’s belief in a language organ, or any of his particular ways of characterizing syntax, or his belief that language is primarily an instrument of thought and only secondarily one of communication.

[...] And on the other matter, linguistics as a field has been very welcoming to women and to people of many different nationalities and ethnicities. Not 100% perfect, of course, but very good relative to many fields.

‬‬What, then, is the point of all this discussion of a few casual remarks?

On the one hand, whatever performative stance Golumbia was taking in making these remarks, one can reasonably take them as empirical. While I haven’t come close to an empirical demonstration on these matters, I have established that the situation is more complex than Golumbia allows for. In particular, and following Jacobson’s suggestion, his remarks collapse once their motivating binary-distinction is dissolved. If that distinction is poorly motivated then it has no value as a guide to ideological biases of researchers in various demographic categories.

* * * * *

My overall impression of Golumbia’s work is not favorable. Perhaps the rest of the book is better. But on the specific matters I have examined, I find his views have only a tenuous relationship with reality, if I may be so naïve as to assert the existence of such a thing.

Golumbia fails to consider the difference between the abstract study of computation and the creation and use of real computational devices. That leads him to conflate the real computational investigation of language, and the creation of practical language tools, with the abstract theory of computation. Is Golumbia’s inability to distinguish between the concrete and the abstract ideologically motivated? I do not know. But it would explain why he fails to see the difference between a hierarchy of abstract objects, the Chomsky Hierarchy, and the operation of hierarchical power in the social world. Is that why he offers an ideological fantasy about a specific political act, the defunding of research in MT, when there is historical evidence about the real politics involved? I do not know. Nor do I know why he offered casual remarks about the demographics of the discipline of linguistics without any evidence.

I do know, however, that his treatment of matters about which I have some knowledge – and first hand experience, is so bad that I am unwilling to trust him on other matters. His logic of the ideology of Chomsky and CL fails to compute.

Pauline Jacobson: ‪Back to Avery's last comment: To the extent that linguistics - including many parts of formal linguistics - is a lot better for and to women many other technical fields, I would not guess that this had much to do personally with Chomsky and Halle. My own guess - and just a guess - is that part of it is that it allows for people who are mathematically inclined but have no formal math background. I'm speaking from personal experience here. I discovered (through linguistics) that I really liked 'mathematical thinking' (I ran away from that in high school... don't ask....) but I had zero formal math training. So Ling. was an incredible place for me. Many women - especially in earlier times - also had little formal math training for whatever reason - partly because they were discouraged (that was not) the case for me). And for such women (and men too, of course) who nonetheless had a formal bent, ling. was a happy place. Along these lines, it had a kind of combination of 'language arts' and science - so the language-y part of it also made it fit with a lot of women's training and self-conception. Finally, getting back to Avery's comment about pre-Chomsky - much of Ling did in those days come from Anthro, and I suspect that anthro was a reasonably friendly place for women in an era where few fields were. But that is pure guess.‬‬‬‬‬‬‬

[2] Martin Kay, David G. Hays, in John Hutchins, ed. Early Years in Machine Translation: Memoirs and Biographies of Pioneers, Amsterdam/Philadelphia: John Benjamins Publishing Company, 2000, pp. 165-170.

This is what I am citing. However each chapter is a different document and there are no page numbers. Here I am citing chapter 4, “Groups and projects in the United States (1950-1966)”: http://www.hutchinsweb.me.uk/PPF-4.pdf